Selected Publications

Journal Articles

  1. Dongsu Lee, Minhae Kwon, “Stability Analysis in Mixed-autonomous Traffic with Deep Reinforcement Learning,” IEEE Transactions on Vehicular Technology, vol 72, no. 3, 2023. [PDF][Media1] [Media2]
  2. Sujin Ahn, Minhae Kwon, “Reproduction Factor Based Latent Epidemic Model Inference: A Data-driven Approach Using COVID-19 Datasets,” IEEE Journal of Biomedical and Health Informatics, vol 27, no.3, 2023. [PDF][Media1] [Media2]
  3. Hyoseon Kye, Miru Kim, Minhae Kwon, “Hierarchical Detection of Network Anomalies: A Self-supervised Learning Approach,” IEEE Signal Processing Letters, vol. 29, 2022. [PDF] [Video] [Media1] [Media2]
  4. Nayoung Kim, Minhae Kwon*, Hyunggon Park*, “Curriculum Reinforcement Learning for Cohesive Team in Mobile Ad Hoc Networks,” IEEE Communications Letters, vol.26, no.8, August 2022. (* co-corresponding authors) [PDF]
  5. Zhengwei Wu, Minhae Kwon, Saurabh Daptardar, Paul Schrater, Xaq Pitkow, “Rational Thoughts in Neural Codes,” PNAS (Proceedings of the National Academy of Sciences of the United States of America), vol.117, no.47, pp.29311-29320, November 2020.[Media1], [Media2]
  6. Minhae Kwon, Juhyeon Lee, Hyunggon Park, “Intelligent IoT Connectivity: Deep Reinforcement Learning Approach,” IEEE Sensors Journal, vol.20, no.5, pp.2782 – 2791, March 2020. [PDF]
  7. Minhae Kwon, Hyunggon Park, “Distributed Topology Design for Network Coding Deployed Large-scale Sensor Networks,” Signal Processing, vol.165, pp.380-392, December 2019. [PDF] 
  8. Minhae Kwon, Hyunggon Park, “Network Coding Based Evolutionary Network Formation for Dynamic Wireless Networks,” IEEE Transactions on Mobile Computing, vol.18, no.6, pp.1316 – 1329, June 2019. [PDF] 
  9. Minhae Kwon, Hyunggon Park, “Distributed Network Formation Strategy for Network Coding Based Wireless Networks,” IEEE Signal Processing Letters, vol.24, no.4, pp.432-436, April 2017. [PDF]
  10. Minhae Kwon, Hyunggon Park, Nikolaos Thomos, Pascal Frossard, “Approximate Decoding for Network Coded Inter-dependent Data,” Signal Processing, vol.120, pp.222-235, March 2016.

Conference Proceedings

  1. Hyoseon Kye, Minhae Kwon, “Partial Federated Learning Based Network Intrusion System for Mobile Devices,” ACM International Symposium on Mobile Ad Hoc Networking and Computing (ACM MobiHoc), October 2022.
  2. Hyoseon Kye, Miru Kim, Minhae Kwon, “Hierarchical Autoencoder for Network Intrusion Detection,” IEEE International Conference on Communications (IEEE ICC), May 2022. [Media1] [Media2]
  3. Minhae Kwon, Saurabh Daptardar, Paul Schrater, Xaq Pitkow, “Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics,” Conference on Neural Information Processing Systems (NeurIPS), December 2020. [Video] [Media1], [Media2]
  4. Minhae Kwon, Hyunggon Park, “Network Coding-based Distributed Network Formation Game for Multi-source Multicast Networks,” IEEE International Conference on Communications (IEEE ICC), May 2017. [PDF] [Slides]
  5. Minhae Kwon, Hyunggon Park, “Analysis on Decoding Error Rate of Systematic Network Coding,” IEEE International Conference on Communications and Electronics (IEEE ICCE), January 2017. [Video][Slides] (Best Poster Video Award)
  6. Minhae Kwon, Hyunggon Park, Pascal Frossard, “Compressed Network Coding: Overcome All-Or-Nothing Problem in Finite Field,” IEEE Wireless Communications and Networking Conference (IEEE WCNC), April 2014. [PDF] [Slides]

Machine Learning Workshop Papers/ Neuroscience Conference Abstracts

  1. Sujin Ahn, Minhae Kwon, “A Markov Chain Based Compartmental Model for COVID-19 in South Korea” Conference on Neural Information Processing Systems (NeurIPS) Machine Learning in Public Health (MLPH) Workshop, December 2021. [Poster]
  2. Sujin Ahn, Minhae Kwon, “Data-driven Markov Chain Model for COVID-19 Transmission in South Korea” Conference on Neural Information Processing Systems (NeurIPS) NewInML Workshop, December 2021. [Video]
  3. Dongsu Lee, Minhae Kwon, “Stability Analysis in Mixed-Autonomous Traffic with Deep Reinforcement Learning,” Conference on Neural Information Processing Systems (NeurIPS) Deep Reinforcement Learning (DeepRL) Workshop, December 2021. [Media][Video]
  4. Sujin Ahn, Minhae Kwon, “A Data-driven Approach to Infer Latent Dynamics of COVID-19 Transmission Model,” Conference on Neural Information Processing Systems (NeurIPS) Women in Machine Learning (WiML) Workshop, December 2021. [Video]
  5. Hyoseon Kye, Minhae Kwon, “PCA-based Low-complexity Anomaly Detection for Low-end IoT Devices,” Conference on Neural Information Processing Systems (NeurIPS) Women in Machine Learning (WiML) Workshop, December 2020. [Poster] [Media]
  6. Minhae Kwon, Saurabh Daptardar, Paul Schrater, Xaq Pitkow, “Inverse Rational Control in Continuous Problems,” Computational and Systems Neuroscience (Cosyne), 2020.
  7. Minhae Kwon, Juhyeon Lee, Hyunggon Park, “Learning To Activate Relay Nodes: Deep Reinforcement Learning Approach,” Conference on Neural Information Processing Systems (NeurIPS) Deep Reinforcement Learning Workshop, 2018.
  8. Minhae Kwon, Juhyeon Lee, Hyunggon Park, “Self-activating Relay Nodes for Emergent Communications,” Conference on Neural Information Processing Systems (NeurIPS) Emergent Communication Workshop, 2018. (selected as oral presentation)

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